Exploring the Potential of Cluster Analysis in Identifying Disease Phenotypes in Calcium Pyrophosphate Deposition:...

Calcium pyrophosphate deposition (CPPD) disease is a heterogeneous condition and is frequently misdiagnosed due to the different clinical presentations and variable disease progression. Aim of this study is to identify clinical phenotypes of CPPD disease by integrating real-world data from two data sets.

Data from the COLCHICORT trial and CHRONIC CPPD European observational cohort were analyzed. Multiple correspondence analysis (MCA) was employed to evaluate and visualize the association between modalities of quantitative variables. Hierarchical clustering on principal components were obtained from MCA-identified clusters based on Ward agglomeration method with Euclidean distance. A bivariate analysis between clusters was then performed to characterize the clusters numerically.

A total of 134 patients were included in the analysis, resulting in four distinct clusters. Cluster 1 had predominantly monoarticular involvement, frequent recurrent flares, older age at onset, female prevalence, and high C-reactive protein (CRP) levels. Cluster 2 also involved monoarticular cases but with persistent arthritis and onset after 60 years, with about half exhibiting elevated CRP. Cluster 3 included polyarticular cases, featuring persistent arthritis and lower CRP levels, whereas cluster 4 highlighted polyarticular involvement (spine and shoulder included) and primarily recurrent flares.

In conclusion, by using for the first time a robust, data-driven methodology based on real-world data, two clusters similar to the EULAR phenotypes "acute CPP crystal arthritis," and "chronic CPP crystal inflammatory arthritis" were confirmed, but in addition, two more clusters that do not correspond to any existing EULAR phenotypes were also identified. Due to the characteristics of the cohorts, the osteoarthritis plus CPPD cluster has not been explored.